Accurate and Fast Federated Learning via IID and Communication-Aware Grouping

no code implementations • 9 Dec 2020 • Jin-woo Lee, Jaehoon Oh, Yooju Shin, Jae-Gil Lee, Se-Young Yoon

Federated learning has emerged as a new paradigm of collaborative machine learning; however, it has also faced several challenges such as non-independent and identically distributed(IID) data and high communication cost.

Federated Learning

Accurate and Fast Federated Learning via Combinatorial Multi-Armed Bandits

no code implementations • 6 Dec 2020 • Taehyeon Kim, Sangmin Bae, Jin-woo Lee, Seyoung Yun

Federated learning has emerged as an innovative paradigm of collaborative machine learning.

BIG-bench Machine Learning Federated Learning +1

TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture

no code implementations • 6 Dec 2020 • Jin-woo Lee, Jaehoon Oh, Sungsu Lim, Se-Young Yun, Jae-Gil Lee

Federated learning has emerged as a new paradigm of collaborative machine learning; however, many prior studies have used global aggregation along a star topology without much consideration of the communication scalability or the diurnal property relied on clients' local time variety.

Federated Learning